The e-ROSA project seeks to build a shared vision of a future sustainable e-infrastructure for research and education in agriculture in order to promote Open Science in this field and as such contribute to addressing related societal challenges. In order to achieve this goal, e-ROSA’s first objective is to bring together the relevant scientific communities and stakeholders and engage them in the process of coelaboration of an ambitious, practical roadmap that provides the basis for the design and implementation of such an e-infrastructure in the years to come.
This website highlights the results of a bibliometric analysis conducted at a global scale in order to identify key scientists and associated research performing organisations (e.g. public research institutes, universities, Research & Development departments of private companies) that work in the field of agricultural data sources and services. If you have any comment or feedback on the bibliometric study, please use the online form.
You can access and play with the graphs:
- Evolution of the number of publications between 2005 and 2015
- Map of most publishing countries between 2005 and 2015
- Network of country collaborations
- Network of institutional collaborations (+10 publications)
- Network of keywords relating to data - Link
Hypoxia due to waterlogging adversely affects agricultural crops in many parts of the world and severely impacts overall annual production levels. To evaluate the response of wheat roots to a controlled hypoxic environment at the level of transcription, a cDNA library was constructed using hypoxia-stressed wheat. A total of 1274 clones (94.8%) out of 1344 sequences were found to be at least 50 bp long. Phrap assembly using high quality sequences formed 879 sets of non-overlapping sequences. Based on BLASTx analysis against the nonredundant database, a total of 494 unigenes showed a high homology to the registered amino acid sequences of plant (E < e(-10)). A total of 112 unigenes, which were not matched to any wheat ESTs in the database, were detected. A functional classification of 118 clones whose transcript levels were evaluated under hypoxia was performed according to gene ontology. These results may provide useful information for further investigations to better understand the response of wheat roots to waterlogging.
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